Identifying High-Risk Events for COVID-19 Transmission: Estimating the Risk of Clustering Using Nationwide Data

Author:

Ueda Minami1ORCID,Hayashi Katsuma1,Nishiura Hiroshi1ORCID

Affiliation:

1. School of Public Health, Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan

Abstract

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be overdispersed, meaning that only a fraction of infected cases contributes to super-spreading. While cluster interventions are an effective measure for controlling pandemics due to the viruses’ overdispersed nature, a quantitative assessment of the risk of clustering has yet to be sufficiently presented. Using systematically collected cluster surveillance data for coronavirus disease 2019 (COVID-19) from June 2020 to June 2021 in Japan, we estimated the activity-dependent risk of clustering in 23 establishment types. The analysis indicated that elderly care facilities, welfare facilities for people with disabilities, and hospitals had the highest risk of clustering, with 4.65 (95% confidence interval [CI]: 4.43–4.87), 2.99 (2.59–3.46), and 2.00 (1.88–2.12) cluster reports per million event users, respectively. Risks in educational settings were higher overall among older age groups, potentially being affected by activities with close and uncontrollable contact during extracurricular hours. In dining settings, drinking and singing increased the risk by 10- to 70-fold compared with regular eating settings. The comprehensive analysis of the COVID-19 cluster records provides an additional scientific basis for the design of customized interventions.

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

Health Care Science Institute

Health and Labor Sciences Research

Japan Agency for Medical Research and Development

Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan, Kao Health Science Research

Daikin GAP fund program of Kyoto University

Collaboration Grant from LEBER

Japan Science and Technology Agency (JST) SICORP program

RISTEX program for Science of Science, Technology and Innovation Policy

Publisher

MDPI AG

Subject

Virology,Infectious Diseases

Reference93 articles.

1. World Health Organization (2022, March 23). WHO Coronavirus (COVID-19) Dashboard. Available online: https://covid19.who.int.

2. The Positive Impact of Lockdown in Wuhan on Containing the COVID-19 Outbreak in China;Lau;J. Travel Med.,2020

3. International Monetary Fund (2021, December 28). World Economic Outlook, April 2020: The Great Lockdown. Available online: https://www.imf.org/en/Publications/WEO/Issues/2020/04/14/weo-april-2020.

4. Effects of the COVID-19 Pandemic and Nationwide Lockdown on Trust, Attitudes Toward Government, and Well-Being;Sibley;Am. Psychol.,2020

5. National Institute of Infectious Diseases, Japan (2021, December 20). Guideline for Execution of Active Epidemiological Investigation on Patients Infected to COVID-19 (Edition as of 12 March 2020), Available online: https://www.niid.go.jp/niid/images/epi/corona/2019nCoV-02-200312.pdf.

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